Overcoming Structural Constraints to Patient Utilization of Electronic Medical Records: A Critical Review and Proposal for an Evaluation Framework
Bibliographic record
Abstract
There are constraints embedded in medical record structure that limit use by patients in self-directed disease management. Through systematic review of the literature from a critical perspective, four characteristics that either enhance or mitigate the influence of medical record structure on patient utilization of an electronic patient record (EPR) system have been identified: environmental pressures, physician centeredness, collaborative organizational culture, and patient centeredness. An evaluation framework is proposed for use when considering adaptation of existing EPR systems for online patient access. Exemplars of patient-accessible EPR systems from the literature are evaluated utilizing the framework. From this study, it appears that traditional information system research and development methods may not wholly capture many pertinent social issues that arise when expanding access of EPR systems to patients. Critically rooted methods such as action research can directly inform development strategies so that these systems may positively influence health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.430 | 0.495 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".